Sensor management for PRF selection in the track-before-detect context

We consider the pulse repetition frequency (PRF) selection problem for target tracking in the context of track-before-detect. Two sensor management criteria are proposed for solving the PRF selection problem. From the information theoretic class, a Kullback-Leibler divergence based criterion is employed and from the task based class, a criterion that is based on the covariance matrix of the posterior density. The proposed sensor management criteria succeed in resolving the ambiguities, avoid choosing a PRF that would place the target in a blind zone and they both produce an unexpected but interesting aspect in the results. That is, they can prevent ambiguities from reappearing due to the motion model without being explicitly designed to handle this unpredicted problem.